Organotypic liver culture models: Meeting current challenges in toxicity testing

Abstract

Prediction of chemical-induced hepatotoxicity in humans from in vitro data continues to be a significant challenge for the pharmaceutical and chemical industries. Generally, conventional in vitro hepatic model systems (i.e. 2-D static monocultures of primary or immortalized hepatocytes) are limited by their inability to maintain histotypic and phenotypic characteristics over time in culture, including stable expression of clearance and bioactivation pathways, as well as complex adaptive responses to chemical exposure. These systems are less than ideal for longer-term toxicity evaluations and elucidation of key cellular and molecular events involved in primary and secondary adaptation to chemical exposure, or for identification of important mediators of inflammation, proliferation and apoptosis. Progress in implementing a more effective strategy for in vitro-in vivo extrapolation and human risk assessment depends on significant advances in tissue culture technology and increasing their level of biological complexity. This article describes the current and ongoing need for more relevant, organotypic in vitro surrogate systems of human liver and recent efforts to recreate the multicellular architecture and hemodynamic properties of the liver using novel culture platforms. As these systems become more widely used for chemical and drug toxicity testing, there will be a corresponding need to establish standardized testing conditions, endpoint analyses and acceptance criteria. In the future, a balanced approach between sample throughput and biological relevance should provide better in vitro tools that are complementary with animal testing and assist in conducting more predictive human risk assessment.

Keywords::

• in vitro hepatic models
• hepatocytes
• hepatotoxicity
• organotypic culture models
• microfluidic devices
• toxicity testing

Acknowledgements

The authors thank Philip Lee (CellASIC), Salman Khetani (Hepregen), Martin Yarmush and Eric Novik (Hµrel), and Dawn Applegate (RegenMed) for providing background information and materials for respective technology platforms represented in Section “Advanced organotypic culture technologies” of this manuscript. Figure 5E was used with permission from the Royal Society of Chemistry (RSC) (Domansky et al., 2010). The authors thank Dr. Lola Reid, University of North Carolina at Chapel Hill, for the illustration used in Figure 7, and John Jackson and Karli E. Stephenson of Life Technologies for their assistance with preparation of figures and final editing.

Declaration of interests

The authors’ affiliations are as shown on the cover page. The contribution of ELL and MEA in this work was supported by the Long-Range Research Initiative (LRI) of the American Chemistry Council (ACC). The authors alone are responsible for the content and writing of the paper and have no conflicts of interest to declare.

Appendix: Abbreviations

ADME, absorption, distribution, metabolism, excretion; AE2, anion exchange protein 2; AhR, aryl hydrocarbon receptor; AQP, aquaporin protein; APAP, acetaminophen; APC, antigen-presenting cells; AUC, area under the curve; CAR, constitutively active receptor; CCL21, chemokine (C-C motif) ligand 21; CCR5, C-C chemokine receptor type 5; CFTR, cystic fibrosis transmembrane conductance regulator; CINC-1, cytokine-induced neutrophil chemoattractant-1; CS-PG, chondroitin sulfate proteoglycans; CTGF, connective tissue growth factor; CYP, cytochrome P450; DILI, drug-induced liver injury; ECM, extracellular matrix; EGF, epidermal growth factor; ET-1, endothelin-1; FGF, fibroblast growth factor; GAG, glycosaminoglycan; GGT, γ-glutamyltranspeptidase; GSH, reduced glutathione; HC, hepatocytes; HCI, high-content imaging; HGF, hepatocyte growth factor; HMGB-1, high-mobility group box-1; HPC, hepatic progenitor cells; HP-PG, heparin proteoglycans; HSC, hepatic stellate cells; HS-PG, heparan/heparin-sulfate proteoglycans; HTS, high-throughput screening; IGF-I and II, Insulin-like growth factor I and II; IHL, intrahepatic lymphocytes; lhx2, LIM homeobox gene 2; IL, interleukin; iPSC, induced pluripotent stem cells; IVIVE, in vitro-in vivo extrapolation; KC, Kupffer cells; LC-MS, liquid chromatography-mass spectroscopy; LPS, lipopolysaccharide; LSEC, liver sinusoidal endothelial cells; MAPC, multipotent adult progenitor cells; MAPK, MAPKK, mitogen-activated protein kinases; 3MC, 3-methylcholanthrene; M-CSF, macrophage colony-stimulating factor; MCP, monocyte chemotactic peptide; MHC, major histocompatibility complex; MIP-2, macrophage inflammatory protein-2; MOA, mode of action; NAPQI, N-acetyl-p-benzoquinoneimine; NKC, natural killer cells; NPC, nonparenchymal cells; MSC, mesenchymal stem cells; PAPS, 3′-phosphoadenosine-5′-phosphosulfate; PB, phenobarbital; PBPK, physiologically-based pharmacokinetic; PDGF, platelet-derived growth factor; PG, proteoglycans; PLT, platelets; PMN, polymorphonuclear leukocytes; PPAR, peroxisome proliferator-activated receptor; PSC, pluripotent stem cells; PXR, pregnane X receptor; QSAR, quantitative structure–activity relationships; RANTES, regulated on activation normal T-cell expressed and secreted; RES, reticuloendothelial system; RLEC, rat liver epithelial cells; SLC4A2, solute carrier family 4 member 2; TAT, tyrosine aminotransferase; TGF-α, transforming growth factor α; TLR, toll-like receptors; TNF-α, tumor necrosis factor α; TGF-α, transforming growth factor α; αSMA, alpha-smooth muscle actin; UDPGA, uridine 5′-diphospho-glucuronic acid; UDP-GT, Uridine 5′-diphospho-glucuronosyl transferase.